EnergyManagementThroughPeakShavingandDemandResponse:
NewOpportunitiesforEnergySavingsatManufacturingandDistributionFacilities
By:NasserKutkut,PhD,DBA
AdvancedChargingTechnologiesInc.
Introduction
Energy efficiency initiatives are increasingly making their way into many manufacturing
and distribution facilities as part of corporate initiatives to reduce energy use, costs and
also meet sustainability goals. Various strategies can be employed to manage energy
usage at industrial and manufacturing facilities such as peak shaving and demand
response. This white paper will highlight the key aspects of peak shaving and demand
response. In addition, the paper will also highlight Advanced Charging Technologies’
products and solutions supporting energy management programs.
Understanding the Electric Bill
For large users, such as manufacturing and distribution facilities, the electricity bill
consists of two components: energy consumption and demand charges (Fig. 1).
Energy
consumption
Energy
Bill
Demand
charges
TotalEnergyCharges
Fig. 1: Components of electricity bill
•
Energy consumption: The total amount of electricity used measured in kWh.
Energy consumption is a straightforward aggregation of the energy used
regardless of the instantaneous power variations. While energy consumption
rates may vary between summer and winter months as well as between day and
night hours, these variations are typically small.
•
Demand Charges: Demand is a measure of the rate at which energy is
consumed. Demand charges are monthly charges based on the highest 15minute monthly peak within a 12-month period, which is measured in kW
(kilowatt). Demand charges typically account for 30–70% of an electricity bill
and differ by season and time of the day. Demand charges are quite higher in
©AdvancedChargingTechnologiesInc.
1
the summer months as compared to winter months as well as day hours versus
night hours.
Fig. 2: Demand charges
One can use the analogy of filling a 5-gallon bucket of water using a low flow versus a
high flow faucet as shown in Fig. 3. The low flow faucet fills the bucket slower than the
high flow faucet. The flow rate is the equivalent to demand while the 5 gallons of
water are equivalent to consumption. While filling both buckets has the same
“consumption”, they have very different “demands.”
Fig. 3: Energy components analogy
An example of the difference between energy consumption costs and demand charges
is shown in the table below.
Customer A
Load: 50kW load for 50 hours
Usage:
§ Energy = 50 kW x 50 hrs = 2,500
kWh
§ Demand = 50 kW
Bill:
§ Energy = 2,500 kWh x $0.15 = $375
§ Demand = 50kW x $28.00 = $1,400
TOTAL = $375 + $1,400 = $1,775
Customer B
Load: 5kW load for 500 hours
Usage:
§ Energy Used = 5 kW x 500 hrs = 2,500
kWh
§ Demand = 5 kW
Bill:
§ Energy = 2,500 kWh x $0.15 = $375
§ Demand = 50kW x $28.00 = $140
TOTAL = $375 + $140 = $515
While both customers use the same amount of energy, namely 2,500 kWh, customer A
demand is higher than customer B, namely 50kW versus 5kW. As such, the demand
charges for customer A are quite higher resulting in higher energy bill.
©AdvancedChargingTechnologiesInc.
2
The Nature of Electric Demand
The electric demand in a power system reflects the aggregate demand of all loads
connected to the distribution network. In a typical power system, adequate generation
capacity is installed to meet the peak demand of the system (Fig. 4). Grid operators
must meet peak demand reliably with all available generation resources. An increase in
peak demand can be met with a corresponding increase in supply-side power, which
may entail building additional generation, transmission, and distribution networks. On
the other hand, the increased peak demand can also be met with a reduction in
demand-side power through load curtailment and shifting to lower peak periods.
Fig. 4: Supply and demand in a power distribution system
From a user perspective, demand kW usage is dictated by the type and number of
loads and equipment operated at a given point in time. Demand kW usage varies
throughout the day and throughout the year. Fig. 5 shows a sample demand curve over
a 24-hour period.
600
AverageDemand=380kW
@$8/kW
500
kW
400
PeakDemand=520kW
@$16/kW
BaseDemand=300kW
@$8/kW
300
200
100
0:15
1:30
2:45
4:00
5:15
6:30
7:45
9:00
10:15
11:30
12:45
14:00
15:15
16:30
17:45
19:00
20:15
21:30
22:45
0:00
0
Time
Fig. 5: Sample daily demand curve
©AdvancedChargingTechnologiesInc.
3
As shown in Fig. 5, the base (minimum) demand over a 24-hour period is 300kW and
the corresponding rate for 300kW peak demand is $8/kW. The average demand is
slightly higher than the base demand, namely 380kW and the demand charge rate is
still the same. However, the peak demand is 520kW and the corresponding rate for
such level of demand is $16/kW.
Note that the peak demand is typically determined based on the maximum amount of
electricity drawn from the grid or over a short period of time, typically 15 minutes. When
customers are billed for demand charges, they are billed based on the highest amount
of demand registered during the billing period (the peak demand) as shown in Fig. 6.
600
Endofbillingperiod
Startofbillingperiod
560kW
500
kW
400
300
200
100
2/11/16
2/9/16
2/7/16
2/5/16
2/3/16
2/1/16
1/30/16
1/28/16
1/26/16
1/24/16
1/22/16
1/20/16
1/18/16
1/16/16
1/14/16
1/12/16
1/10/16
1/8/16
1/6/16
1/4/16
0
Demand
MaxDemand
Fig. 6: Typical demand curve over a billing period showing peak demand for the period
Time of Use Rates (TOU)
The electricity prices that large end users pay depend on the time of day energy is used
as well as the season. Typically, there are three different rates corresponding to three
time periods, namely:
§
§
§
On-peak (highest price)
Semi-peak (lower price)
Off-peak (lowest price)
The table below shows sample on-peak, semi-peak, and off-peak periods for a typical
utility.
Summer (Ex: May 1 to October 31)
Winter (Ex: November 1 to April 30)
On-Peak
11am – 6pm (Mon. to Fri.)
5pm – 8pm (Mon. to Fri.)
PartialPeak
6am – 11am, 6pm – 10pm (Mon. to
Fri.)
6am – 5pm, 8pm – 10pm (Mon. to
Fri.)
Off-Peak
10pm – 6am (Mon. to Fri.)
Weekends and holidays
10pm – 6am (Mon. to Fri.)
Weekends and holidays
©AdvancedChargingTechnologiesInc.
4
TOU rates are typically reflected on the customer’s energy bill. The table below shows
a sample monthly electric bill with itemized TOU charges.
Season: Summer
On-Peak
Partial-Peak
Off-Peak
Total Energy Cost
Season: Summer
Max. On-Peak
Max. Partial-Peak
Max. Off-Peak
Total Demand Charges
Energy
37,048.000 @ $0.23357
31,319.000 @ $0.09502
58,381.000 @ $0.06978
$11,998
Demand
362.000 @ $14.5900
361.000 @ $3.41000
361.000 @ $11.85000
$10,802
As shown from the above table, the on-peak energy rates are quite high, almost 3 times
off peak rates. The on-peak demand rates are even higher, almost 4 to 5 times the offpeak rates. In some areas, the on-peak demand rates can be 10 or 15 times higher the
off-peak rates prompting users to action to reduce their on-peak demand.
Reducing Peak Demand: Peak Shaving
One way to reduce peak demand is to control or reduce electrical usage during periods
of maximum demand on the power utility. This allows end users to reduce demand
penalties and the corresponding demand charges during peak periods. In addition,
peak shaving also helps the utility provide maximum base load power without starting
expensive to operate peaking generators. As such, utilities may also offer incentives to
customers implementing peak shaving programs. In fact, C&I customers can realize
10% - 30% in demand cost savings depending on the type of loads and flexibility of the
loads. Fig. 7 shows an example of daily peak shaving via load management.
CurrentDemand(kW)
$Saved
NewDemandwith
PeakShaving(kW)
Midnight6am9amnoon3pm6pm9pmMidnight
Fig. 7: Reducing peak demand through peak shaving
©AdvancedChargingTechnologiesInc.
5
Peak shaving can be realized using several ways including1:
§
Load Shedding: Entails switching off loads during periods of maximum peak
demands. Facility managers typically identify sheddable loads, which can easily be
turned off and restarted without serious impact on processes or staff. Typical
sheddable loads include HVAC systems, non-sensitive industrial machines, and
some lighting.
§
Adding Capacity via On-Site Generation: For sites with limited sheddable loads,
facility managers can add capacity using on-site generation to increase available
power without increasing demand. Renewable energy sources – such as solar PV,
and battery energy storage – are slowly becoming favorites for peak shaving
programs due to its fast dispatchable nature and ease of control.
Demand Response (DR) Programs
Demand Response (DR) is a class of demand-side management programs in which
utilities offer commercial and industrial (C&I) customers incentives to reduce their
demand for electricity during periods of critical system conditions or periods of high
market power costs. DR focuses on reducing demand temporarily in response to a price
changes or other type of incentive, particularly during the system’s peak periods. Endusers receive compensation – either through utility incentives or rate design – to reduce
non-essential electricity use or to shift electric load to a different time, without
necessarily reducing net usage. Fig. 8 shows an example of a demand response event
where a customer reduces their peak demand by almost 300kW from a baseline of
1,285kW to 965kW during the hours of 2:00 pm to 4:00 pm.
Fig. 8: An example of DR events
Demand response programs can be realized using several ways including load
shedding, load shifting, and load displacement (Fig. 9).
1
SchneiderElectric:ReducingEnergyCostswithPeakShavinginIndustrialEnvironments
©AdvancedChargingTechnologiesInc.
6
CustomerDailyDemand(kW)
Shiftingloads
tooff-peak
Loadsheddingor
displacement
duringpeakhours
Midnight3:006:009:00Noon3:006:009:00Midnight
a.m.a.m.a.m.p.m.p.m.p.m.
TimeofDay
Fig. 9: Peak load management options
§
Load Shedding: Similar to peak shaving, non-critical loads are switched off during
periods of maximum peak demands. For example, office lighting and non0critical
office equipment can be switched off during DR events.
§
Load Shifting: This entails moving consumptions to time periods outside the DR
event or when the price of electricity is lower. For example, cold storage facilities
can shift their load and reduce peak demands by pre-cooling their refrigerators to a
lower temperature prior to the DR event, then allowing the temperature to rise
naturally. Proper temperature monitoring will ensure that product quality is not
compromised.
§
Load Displacement: This entails offsetting peak demand with on-site generation
such as renewable sources and battery energy storage.
DR End User’s Benefits
C&I customers can enjoy many benefits from implementing DR programs including2:
§
DR Payments. Utility customers get paid, in cash or as bill credits, for participating
in DR programs. Some utilities offer a payment for enrolling as well as a payment
per event
§
Reduced Power Consumption. Customers can reduce their power consumption
and energy costs if their DR actions lead less overall electricity usage.
§
Lower Energy Market Prices. Reducing demand during peak times minimizes
utilities’ need to secure energy from more expensive sources such as peaking
generators or spot markets. As such, electricity rates are reduced as well.
§
Payments for DR Equipment. Some programs compensate participants for
installing automated controls that can assist with carrying out DR measures.
2
CEATIInternational:DemandResponseforSmalltoMidsizeBusinessCustomers–ReferenceGuide
©AdvancedChargingTechnologiesInc.
7
§
Enhanced Energy Security. Energy security is a critical benefit of demand
response. Blackouts impose tremendous economic and social costs, including
equipment damage, lost revenue from damaged or spoiled products, lost wages and
reduced productivity.
Dynamic Energy Management
Dynamic Energy Management is an innovative approach to managing energy at the
demand-side (end user). It incorporates the conventional energy use management
principles such as peak shaving, demand response, and distributed energy resource
programs and merges them in an integrated framework that results into permanent
energy savings, demand reductions, and short term peak load reductions3.
Dynamic Energy Management is accomplished through a system is comprised of smart
end-use devices (e.g. smart appliances), highly advanced controls, and integrated
communications capabilities that enable dynamic management of the overall system
(Fig. 10). These components build upon and interact with one another to realize a
dynamic infrastructure that is fully-integrated, highly energy efficient, automated, and
capable of learning.
•
Smart Appliances: These are intelligent equipment and devices equipped with
embedded controls, two-way communications, and automated control. Industrial
appliances are typically highly efficient, internet protocol (IP) addressable, and
can be controlled by external signals from the utility, end-user, or other
authorized entity.
IntegratedCommunication
Architecture
AdvancedControlSystems
SmartEnd-UseDevices
(SmartAppliances)
Fig. 10: Dynamic energy management components
•
Integrated Communication Architecture: This entails an integrated open
architecture communication system that enable interoperability and
communications between devices. Such system allows automated control of the
smart appliances in response to external signals and commands such as pricing
or emergency demand reduction signals from the utility.
3
“DynamicEnergyManagement,”2008ACEEESummerStudyonEnergyEfficiencyinBuildings.
©AdvancedChargingTechnologiesInc.
8
ACT Quantum Chargers’ Energy Management Capabilities
The Quantum charger, ACT’s flagship products, is the industry’s first smart industrial
charger appliance that feature many advanced energy efficiency and energy
management capabilities as well as communication and smart grid integration (Fig. 11).
The Quantum chargers is first industrial smart appliance that is highly efficient, internet
protocol (IP) addressable, and can be controlled by external signals from the utility, enduser, or other authorized entity.
Fig. 11: ACT Quantum chargers: Industry’s first smart charging appliance
Quantum chargers boast high peak efficiencies of > 94% and high charge cycle energy
efficiencies of >93%, greatly reducing the kWh usage and corresponding energy costs.
Further, Quantum chargers incorporate an integrated communication architecture with
two-way wireless communication, allowing for remote monitoring and control as well as
cloud integration. With and open communication network architecture, Quantum data is
easily uploaded to ACT’s ACTview cloud application, allowing users to centrally manage
their charger assets, optimize battery and fleet performance, troubleshoot charger
issues, and implement energy management programs.
Advanced energy management functionalities of Quantum chargers allow end users to
implement and participate in peak shaving and DR programs. Through ACT’s ACTView
cloud application, smart grid integration is facilitated, allowing facility managers to
centrally manage energy usage, implement peak shaving programs, and participate in
DR programs.
Quantum chargers support various energy management functionalities including lockout
modes and static peak shaving schedules (Fig. 12).
•
Lockout Mode: The Quantum chargers can be disabled (not allowed to operate)
during high peak demand periods, which allows for load shifting to other low peak
periods. This mode can be programmed both manually and remotely, and
schedules can be set for specific days of the week or hours of the day.
•
Static Peak Shaving Schedules: In this mode, the maximum output power of
Quantum chargers can be limited during high peak demand periods by setting a
maximum power limit factor (in percentage) for each Quantum charger. This
©AdvancedChargingTechnologiesInc.
9
capability can be programmed both manually and remotely, and schedules can
be set for specific days of the week or hours of the day.
Fig. 12: Quantum charger lockout and static peak shaving programming screen
Additionally, the Quantum chargers support various DR programs including dynamic
peak shaving schedules and DR events.
•
Dynamic Peak Shaving Schedules: The Quantum chargers can be dynamically
programmed for reduced peak power based on customer’s changing demands.
Under dynamic peak shaving, a maximum power limit for the entire charger fleet
can be set where a dynamic peak shaving algorithm dynamically sets and
adjusts the individual maximum power limit for each charger based on the battery
charging needs. For example, deeply discharged batteries will be given priority
where the corresponding charger power limit will be set to maximum while
chargers connected to partially discharge batteries will have lower maximum
power settings.
•
Demand Response / Curtailment: Similar to dynamic peak shaving, Quantum
chargers can dynamically respond to external DR events / curtailment signals to
reduce peak power. Algorithms for optimizing battery fleet charging during
reduced peak power periods are being developed.
The above energy management functions can be programmed locally or remotely
through the ACTview cloud platform (Fig. 13). Future integration is planned with
automated DR through OpenADR, a communications data model designed to facilitate
sending and receiving DR signals between a utility or independent system operator
(ISO) and electric customers.
©AdvancedChargingTechnologiesInc.
10
Fig. 13: Quantum chargers automated DR architecture
Conclusion
Automated energy management technologies can greatly enhance a facility’s ability to
reduce energy consumption and peak load demands through peak shaving and
dynamic DR programs, ultimately realizing greater energy efficiency and cost savings.
C&I customers can achieve energy savings of 20 to 40 percent when automated
technologies are utilized4. Technologies with two-way communication capability can
further enhance the energy savings potential as it enables utilities to verify load
reductions in near-real time.
ACT’s Quantum charger platform is first industrial smart appliance that is highly
intelligent, internet protocol (IP) addressable, and can be remotely controlled, allowing
facility managers to include their charger fleets in their energy management programs.
4
“DemandResponse:AnIntroduction,”RockyMountainInstitute,30April2006.
©AdvancedChargingTechnologiesInc.
11